Journal of Textile Research ›› 2021, Vol. 42 ›› Issue (10): 157-162.doi: 10.13475/j.fzxb.20201205006

• Apparel Engineering • Previous Articles     Next Articles

Clothing style identification based on improved edge detection algorithm

TUO Wu1(), WANG Xiaoyu1, GAO Yakun2, YU Yuanyuan1, HAO Xiaoxiao1, LIU Yongliang1, GUO Xin1   

  1. 1. College of Fashion, Zhongyuan University of Technology, Zhengzhou, Henan 451191, China
    2. College of Electrical Engineering and Automation, Henan Institute of Technology, Xinxiang, Henan 453003, China
  • Received:2020-12-18 Revised:2021-06-29 Online:2021-10-15 Published:2021-10-29

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Abstract:

In order to quickly identify clothing styles and improve production efficiency, an improved edge extraction algorithm was designed to solve the problem that the existing traditional edge detection algorithm was difficult to accurately extract contour feature sequence. By defining a new optimization convolution kernels, the use of traditional edge detection algorithm based on clothing contours of the training sample, will the convolution convolution kernels and target matrix are new outer contour, a new contour sequence of Fourier descriptor as a feature vector, to increase the use of BP neural network model to complete the design of automatic classification and recognition. In order to verify the effectiveness of the improved method, a sample library containing 500 non-repeated clothing images of four categories of clothing was established. 281 samples were selected as training samples and the remaining 219 samples were tested. The recognition accuracy of the test was as low as 93.48% and as high as 100%. It is of reference significance to the intelligent production of clothing.

Key words: clothing style identification, edge detection algorithm, fourier descriptor, BP neural network

CLC Number: 

  • TS941.26

Fig.1

Grayscale image"

Fig.2

Gray scale transformation"

Fig.3

Threshold segmentation"

Fig.4

Morphologically processed images"

Fig.5

Canny algorithm flowchart"

Fig.6

Traditional edge detection of some pixels"

Fig.7

Convolution operation"

Fig.8

Neighborhood pixel with coordinate (0,1) in Y2"

Fig.9

Improved pixel of rear edge detection"

Fig.10

Profile signals between before(a) and after(b) algorithm improvement"

Fig.11

Relationship between eigenvector length of Fourier descriptor and recognition close reading"

Tab.1

Sample collection of clothing style drawings"

服装类
型编号		 测试集款式 总数量 训练集数量 测试集数量
1 连衣裙 116 58 58
2 长裤 116 61 55
3 衬衫 127 66 61
4 短袖 141 96 45

Fig.12

Flow chart of clothing style identification system"

Tab.2

Test sets sample recognition results"

服装类
型编号		 测试集款式 识别率/%
改进前 改进后
1 连衣裙 74.42 95.35
2 长裤 86.84 100.00
3 衬衫 76.09 93.48
4 短袖 73.33 96.67
平均值 77.67 96.375

Tab.3

Comprehensive comparison results"

算法 平均识别率/% 平均运行时间/ms
改进前算法 77.670 84
改进后算法 96.375 98
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